1 Introduction

Aluminum is the second used metal in the world after steel, due to its lightness coupled with its strength, high electrical and thermal conductivities, low density, relatively low cost and high corrosion resistance. Aluminum is used in marine engineering because of the need for light-weight structural materials (Alexopoulos et al. 2012; Dan et al. 2011; Díaz-Ballote et al. 2009). The Al corrosion resistance in aqueous solutions is related to a film formed with air. This film is composed of a porous layer which pores are extending from the outer surface to the metal substrate and also, a rather non porous layer contiguous to the oxide/metal interface. The one of the most used acids in the etching and pickling of aluminum capacitor foil is the hydrochloric acid (HCl) solutions. The acid anion (Cl−) causes the dissociation of passivity via the preparation of oxide–chloride complexes and initiation of the pitting corrosion (El Aal et al. 2013). Corrosion inhibitors are extensively used in corrosion protection of metals and equipment. Organic compounds with functional groups containing nitrogen, sulfur, and oxygen atoms are generally used as corrosion inhibitors. Most of these organic compounds are not only expensive, but also harmful to the environment. Thus, efforts have been directed toward the development of cost effective and nontoxic corrosion inhibitors. Plant products and some other sources of organic compounds are rich sources of environmentally acceptable corrosion inhibitors. Aluminum is prone to corrosion when it is exposed to acids solution. Some research has centered on corrosion resistance of aluminum alloys, using corrosion inhibitors. In the past few years, trying to use of drug compounds as corrosion inhibitors which are eco-friendly and harmless have been developed (Gece 2011).

This work is designed to study Effect of tetracycline and streptomycin (Fig. 1) on inhibition of aluminum corrosion in acid solution by electrochemical techniques, scanning electron microscopy (SEM) and weight loss measurements. Two factor to select the concentration of HCl solution as electrolyte are the high corrosion rate for aluminum in hydrochloric acid and the low thickness of examined samples, which cause the holes in sample by its dissolution at concentrated solution. In this way, the 0.2 M HCl is selected for investigation. In continuing our investigations, we attempt to find the adsorption behavior of tetracycline and streptomycin by the molecule dynamics simulation method and quantum chemical calculations.

Fig. 1
figure 1

Molecular structure of streptomycin (I) and tetracycline (II)

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2 Experimental Procedures

2.1 Materials

The inhibitor molecules (tetracycline and streptomycin) were obtained from Sigma-Aldrich and employed without any further purification.

2.2 Sample Preparation

The metal specimens used in these studies were cut into 20 mm × 20 mm × 1 mm dimensions. Before measurements the samples were polished using different grades of emery paper. The specimens are washed thoroughly with using bi-distilled water degreased and placed in an ultrasonic acetone bath for about 5–10 min for removing possible residue of polishing, dried with acetone. Fresh HCl 0.2 M solution was used as corrosive electrolyte in all the experiments carried out at room temperature.

2.3 Instrumentation

The polarization studies were carried out in an electrochemical conventional cell with triple-electrode and using an Auto lab potentiostat–galvanostat (model PGSTAT 30 Metrohm). The obtained data and equivalent circuits were fitted simulated by Nova 1.11 software. The surface morphology of corroded Aluminum in the absence and presence of antibiotics inhibitors were imaged by a scanning electron microscope (SEM) S4160 FE model Hitachi with 20 kV acceleration.

2.4 Specimens and Solution

Specimens were prepared by cutting commercially available aluminum rod. Prior to each and individual experiment, the metal specimens surfaces were polished with fine emery papers. Then the metallic samples were degreased with ethanol and rinsed with double-distilled water.

2.5 Weight Loss Measurement

The gravimetric study (weight loss method) is recognized to be the most widely used process for monitoring inhibition efficiency (Kairi and Kassim 2013). The easiness and reliability of the result offered by the gravimetric method is such that this technique forms the baseline method of measurement in many programs of corrosion monitoring (Obot et al. 2013). For weight loss measurements, the cleaned Al sheet with dimension of 20 mm × 20 mm × 1 mm was weighed before and after immersion in an open beaker containing the test solution for a period of time up to 3 h. Before testing, all specimens were abraded with sandpapers from number 500 to 1000 grit, cleaned with double distilled water and absolute acetone, dried in the room condition and weighted accurately. After testing, each specimen was taken out and washed carefully in absolute acetone under ultrasound waves until the products of corrosion process, on the surface of specimens were removed thoroughly, then dried in an oven at 70 °C for 30 min and weighed accurately after cooling to room temperature. The weight loss experiments were performed at 296 Kin the known inhibitor (5 ml 1000 ppm in 30 ml) concentration and the HCl. The average weight loss, W, for identical tests was taken and expressed versus mg cm−2.The corrosion rate, A, in g cm−2 h−1 was determined from the relation (El Aal et al. 2013):

$$A = \frac{W}{{({\text{area}} \times {\text{time}})}}.$$
(1)

2.6 Electrochemical Measurements

A cut of aluminum sheet (20 × 20 × 1 mm) was set as working electrode. A platinum electrode and a saturated calomel electrode (SCE) were used as control and reference electrodes, respectively. The working electrode (Al specimens) was polished mechanically, washed with acetone, in dd-water and dried in room condition. All measurements were carried out with freshly polished electrodes and de-aerated in the test solution. The curves of polarization were recorded with 10 mV s−1 sweep rate. To obtain the corrosion current densities, the linear Tafel segment of the cathode and anode curves was extrapolated to the potential of corrosion. In polarization measurements, Stern–Geary equation was employed to calculate the current density for corrosion process in different concentration (Noroozifar et al. 2013):

$$J_{\text{cor}} = \frac{{\beta_{\text{a}} \times \beta_{\text{c}} }}{{2.303 \times R_{\text{p}} \times (\beta_{\text{a}} + \beta_{\text{c}} )}}$$
(2)

whereas J cor is the current density of corrosion, R p is the polarization resistance and β c and β a are the cathode and anode Tafel slopes.

So, the polarization resistance can be measured on the basis of following Eq. (3) (Liping et al. 2006):

$$R_{\text{p}} = \frac{\Delta E}{\Delta J} = \frac{\partial E}{\partial J}.$$
(3)

The corrosion rate (Ratecor) can be obtained from the following Eq. (4) (Ciubotariu et al. 2008):

$${\text{Rate}}_{\text{cor}} = \frac{{3270 \times J_{\text{cor}} \times M}}{D \times V}$$
(4)

which 3270 is 0.01 × [1 year (in s)/96,497.8]; 96,497.8 is 1 Faraday constant in Coulombs]; Ratecor, corrosion rate (mpy); J cor, the current density of corrosion (A cm−2); V, the sample volume (cm3). M, weight (26.98 g) per unit mole and D, sample density (2.70 g cm−3).

Then, inhibition efficiency (IE%) was calculated using J cor as follow (Gopiraman et al. 2012):

$${\text{IE}}(\% ) = \frac{{\left( {J_{\text{cor}}^{\prime } - J_{\text{cor}} } \right)}}{{J_{\text{cor}}^{\prime } }} \times 100$$
(5)

where, J cor and \(J_{\text{cor}}^{{\prime }}\) are the current density for corrosion reaction in solution with and without of inhibitor, respectively.

2.7 Surface Analysis

To get insight into the changes on surface of samples before and after the addition of inhibitors, aluminum specimens used for surface morphological studies were cut into 10 × 10 × 1 mm dimensions. The specimens were first immersed in HCl 0.2 M with and without inhibitors for 24 h, respectively, and washed with bi-distilled water and dried at room temperature.

2.8 Computational Studies

The calculations of quantum chemical were performed through the density functional theory (DFT) for two inhibitors at the B3LYP/6-311++G** level of theory (Becke 1988, 1993; Lee et al. 1988) by the Gaussian 03 series of programs (Frisch et al. 2004). The frequency analysis was performed to ensure that the researched molecules gotten their respective ground state. All the frequencies are found to be positive, which reflects that, the ground state of optimized structures correspond to global minima. To consider the effect of solvent in the calculations. Calculations were conducted under the self-consistent reaction field (SCRF) theory. The solvent (H2O) effect was simulated with using the polarizable continuum model (PCM) for better understanding of the experimental results obtained from the aqueous solution (Miertuš et al. 1981).

Based on the conceptual DFT, global electronic indexes such as: global hardness (η) and electronegativity (χ) are defined as follows (Parr and Pearson 1983; Parr and Yang 1989):

$$\eta = - \left( {\frac{{\partial^{2} E}}{{\partial N^{2} }}} \right)_{v(r)} = \frac{I - A}{2}$$
(6)
$$\chi = - \left( {\frac{\partial E}{\partial N}} \right)_{v(r)} = \frac{I + A}{2},$$
(7)

where A and I are, respectively, the electron affinity and ionization potential. From the values of the total electronic energy, electron affinity (A) and the ionization potential (I) of the inhibitors are calculated using the following equations:

$$I = E_{(N - 1)} - E_{N}$$
(8)
$$A = E_{(N)} - E_{(N + 1)} ,$$
(9)

where \(E_{(N - 1)}\), E (N), and \(E_{(N + 1)}\) are the energies of system ground state with (N − 1), (N) and (N + 1) electrons, respectively.

Electrophilicity is a very useful theoretical parameter that Parr et al. (1999) defined as the changing energy of an electrophile, when it comes in contact with a nucleophile electrophilicity index \((\omega )\) can be found from the descriptions of global hardness and electronegativity as follows:

$$\omega = \frac{{\chi^{2} }}{2\eta }.$$
(10)

The electric dipole polarizability (\(\alpha\)) is as a measurement of the linear response of the electron density in the presence of an infinitesimal electric field F and it descript a second order variation in energy:

$$\alpha = - \left( {\frac{{\partial^{2} E}}{{\partial^{2} F_{a} \partial^{2} F_{b} }}} \right)\quad a,b = x,y,z.$$
(11)

The polarizability (\(\alpha\)) is calculated as the mean value and express through the Eq. (12):

$$\alpha = \frac{1}{3}(\alpha_{xx} + \alpha_{yy} + \alpha_{zz} ).$$
(12)

Molecular dynamics (MD) simulation is as a technique which is popular to studies of interaction between inhibitor and the concerned metal surfaces. In this way, the interaction between an inhibitor and aluminum (Al) surface is investigated by MD simulation with the Forcite module of the Materials Studio 6.0 software developed by Accelrys Inc (Materials Studio 2007). The interaction between Al (1 1 0) surface and inhibitor molecules is carried out in a simulation box (80.99 × 57.26 × 73.54 Å) with periodic boundary conditions. A vacuums slab of 50 Å height is kept over the Al (1 1 0) surface. Non-bonding, van der Waals and the interactions of electrostatic were set as atom-based summations using the Ewald summation method with a cutoff radius of 15.50 Å. Twenty layers of Aluminum atoms was considered. During the simulation procedure all the atoms in the Al (1 1 0) surface were fixed and inhibitors are allowed to interact with the surface of metal freely. The force field used is COMPASS (condensed phase optimized molecular potentials for studies of atomistic simulation) force field.

The MD simulation is performed at 298.0 K under canonical ensemble (NVT) using time step of 1.0 fs and time of simulation equal to 50 ps. The geometry of the system was optimized such that the total system energy was at a local minimum with respect to potential energy. Then, the dynamic process was performed until the entire equilibrium of system obtained, at which both the system and the temperature energy were balanced.

The energy of interaction between the inhibitor molecules and the metal surface were estimated according to the following equation (Materials Studio 2007):

$$E_{\text{int}} = E_{{({\text{total}})}} - (E_{\text{surface}} + E_{\text{inhibitor}} + E_{\text{solution}} ).$$
(13)

3 Results and Discussion

3.1 Potentiodynamic Polarization Measurements

The polarization curves (Tafel) for aluminum sheet were recorded at different concentration of inhibitors (tetracycline (II) and streptomycin (I)) in 0.2 M HCl aqueous solution and potential range between − 1.1 and − 0.4 V vs. SCE (Fig. 2). Table 1 shows the corrosion current density (J cor), Tafel slopes (β a and β c), corrosion potential (E cor), polarization resistance (R p), corrosion rate parameters and the efficiency of inhibition. The current density decreasing was obvious with the inhibitor concentration increasing. The addition of inhibitors to the acidic media affected both anodic and cathodic branches of the Tafel curves. In this electrolyte, the anodic process of corrosion is the passage of metal ions from the surface of aluminum metal into the solution. The principal cathodic process is the reduction of hydrogen ions and the production of H2 gas bubbles. The inhibitor can affect either one or both processes of the cathodic and anodic and in these experiments, the anodic Tafel slope β a and cathodic Tafel slope β c of inhibitors were found to change with inhibitor concentration. Therefore, the suggested compounds can be recognized as an anodic- or a cathodic-type inhibitor. The synergic inhibition effects were observed for both inhibitors by results. The corrosion potential was more shifted to the negative value for both inhibitors and this indicates the inhibitors have more effect on the cathodic half-reaction than the anodic. So, it concluded that the inhibition efficiency for streptomycin is more than tetracycline.

Fig. 2
figure 2

Polarization curves for aluminum sheet in solution of 0.2 M HCl solution at different concentrations of inhibitors (a tetracycline and b streptomycin) at 25 °C in the potential range − 1.1 to − 0.4 V vs. SCE with scan rate 10 mV s−1

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Table 1 Polarization parameters and efficiency of corrosion inhibition (IE%) on aluminum surface by streptomycin and tetracycline in acidic media at 25 °C
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3.2 Gravimetric Study

Table 2 displays the results of weight loss technique of Al sheets corrosion in the known inhibitor (5 ml 1000 ppm in 30 ml) concentration and 0.2 M HCl solution as a time function.

Table 2 Weight loss and corrosion rate for the test solution contains inhibitor for the corrosion of Al sheet at 296 K temperature for two different times
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With comparing the results, it is clear that the corrosion rate was decreased in higher time. It is for this reason that accumulated corrosion products on the metal surface reduce the amount of access to the metal surface through time for corrosive agents.

3.3 Adsorption Isotherm

The adsorption of inhibitors on the metal surface is a substitution reaction between the organic compound in the aqueous phase (Orgaq) with H2O molecules which adsorbed to the aluminum surface, (H2Oads) (Burrows et al. 1976):

$${\text{Org(sol)}} + x{\text{H}}_{2} {\text{O}} \to {\text{Org}}_{\text{ads}} + x{\text{H}}_{2} {\text{O,}}$$
(14)

where x is the size ratio, i.e., the number of H2O molecules replaced by one molecule of organic adsorbate. The (sol)Org and (ads)Org are the fraction of organic molecules that exist in solution form and in adsorbed form on metal surface, respectively (Negm et al. 2012; Shukla and Quraishi 2009).

Adsorption isotherm provides helpful information about the interaction between inhibitor molecules and aluminum surface. Physical adsorption and chemical adsorption are two main types of adsorptions that explain the behaviors of inhibitors. There are several adsorption isotherms (Langmuir, Temkin, Frumkin, etc.) for measuring the metal surface adsorptions. Experimental values obtained from Tafel measurements were graphically investigated for fitting Langmuir, Temkin and Frumkin. According to the Eq. (5), the surface coverage at different inhibitor concentrations, which resulted from inhibition efficiency (IE%), was obtained from Tafel measurements. The correlation coefficient (R 2) was used to decide the isotherm that has the best fit with experimental data and the Temkin isotherm was the best fit with our experiments

$$\ln C = - \ln K + a\theta {\text{Temkin,}}$$
(15)

where the θ is the degree of surface coverage; C is the inhibitor concentration and K ads is the constant of adsorption equilibrium (Golestani et al. 2014; Metikoš-Hukovič et al. 1996).

Thus, our results showed the inhibitors adsorption to the surface obeys the Temkin isotherm (Fig. 3). The equilibrium constant of adsorption (K ads) was derived from the intercepts of plots and, the standard free energy is related to the equilibrium constant of adsorption Eq. (16):

$$\Delta G_{\text{ads}} = - RT\ln (55.5K_{\text{ads}} )$$
(16)

R (J mol−1 K−1) and T are universal gas constant and absolute temperature in Kelvin, respectively. The 55.5 value is the molar concentration of H2O.

Fig. 3
figure 3

Temkin isotherm for aluminum in HCl 0.2 M at different concentrations of (I) and (II). The initial data were obtained from Tafel measurements

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If the value of \(\Delta G_{\text{ads}}^{0}\) is to be near or lower than − 20 kJ mol−1 then, the adsorption type is considered as physisorption; because of electrostatic interactions between charged species and the charged metal. While, if the \(\Delta G_{\text{ads}}^{0}\) value to be near or has more negative value than − 40 kJ mol−1, then it will be considered as chemisorption; that involves the charge sharing or transfer from organic molecules to the metal atoms. In our study, the \(\Delta G_{\text{ads}}^{0}\) value for two inhibitors was negative. So, in accordance with previous reports, this suggests that the adsorption of the inhibitors on Cu sheet surface was a spontaneous process (Wahyuningrum et al. 2008; Zvauya and Dawson 1994). The calculated \(\Delta G_{\text{ads}}^{0}\) values (− 20.18, − 18.71 kJ mol−1) for inhibitors indicate that the adsorption mechanism of inhibitor streptomycin and tetracycline Cu sheet is physisorption.

3.4 Surface Analysis

SEM images of the aluminum surface are taken to establish a link between the surface morphology and the obtained experimental results for the inhibition performance of the inhibitor compounds. The SEM micrographs of aluminum sample after exposure in HCl 0.2 M without inhibitor after 24 h are shown in Fig. 4a, while Fig. 4b, c represents the surface morphology of aluminum specimens immersed in HCl 0.2 M medium containing 0.56 ppm of streptomycin and tetracycline.

Fig. 4
figure 4

SEM images of Al sheet after immersion in HCl 0.2 M for 24 h a in the absence of inhibitor b in the presence of 0.56 mM streptomycin, c in the presence of 0.56 mM tetracycline

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The surface morphology of aluminum sample in the non-inhibited condition is corroded. It is visible some cracks and pits as a result of the corrosive agent attack. Figure 4b, c indicates that with the addition of inhibitors to the solution, the damage has been decreased and the aluminum surface has the less damage in HCl 0.2 M medium containing streptomycin than tetracycline, Therefore, it can be concluded that streptomycin is a better inhibitor than tetracycline for corrosion inhibition of aluminum.

4 Computational Calculations

4.1 Quantum Chemical Calculations

The global parameters hardness (η), electrophilicity (ω), for two inhibitors are compiled in Table 3. It is well established in the literature that a high E HOMO (less negative) is associated with electron donating ability of a molecule to low empty molecular orbital of appropriate acceptor agent and therefore, indicated good performance of the corrosion inhibitor, while, the low E LUMO value indicates that the electron receiving tendency of the molecule. So we computed the E HOMO and E LUMO of inhibitors.

Table 3 Quantum chemical parameters of the studied inhibitors in aqueous phase calculated at B3LYP/6311++G** level
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According to Table 3, the values of E HOMO show the relation (streptomycin > tetracycline) which follows the order of the experimentally determined inhibition efficiency E LUMO values is not compatible with the trend in the efficiency of determined inhibition, experimentally.

According to HSAB principle, bulk metals are chemically the softest materials this would imply that the softest bases inhibitors are most effective for corrosion of these metals. Low hardness values represents that molecule is soft and polarizable. According to the calculated values of global hardness streptomycin has less hardness values compared to tetracycline.

Electrophilicity may be stated as the amount of reactivity towards attracting electrons from a nucleophile of a chemical species. For this reason, it can be stated that a molecule that have great electrophilicity value is ineffective against corrosion while a molecule that have low electrophilicity value is a good corrosion inhibitor.

The trend in the \(\omega\) values for the mentioned inhibitors show streptomycin has the lowest value of electrophilicity. This effect increases the adsorption of inhibitor molecule on the mild steel surface and therefore enhances its corrosion inhibition efficiency when compared to tetracycline.

The tendency of an electron cloud to be distorted from its normal shape is mentioned to as its polarizability. The higher values of the polarizability facilitate the strong adsorption process of corrosion inhibitors onto surface of metal and hence, high inhibition efficiency.

The polarizabilities are evaluated using Eq. (12) and reported in Table 3 for two inhibitors. As can be seen, the trend for the variation of polarizability follows: I > II. These data show that the trend of increasing inhibition efficiencies of the inhibitor molecules with respect to enhancement of polarizability can be consistent well with the order of the experimental % inhibition efficiencies results (I > II).

The dipole moment (μ) is another key electronic factor that results from a non-uniform distribution of charges on the different atoms in the molecule is the most widely used quantity that can also be used for the prediction of the direction of a inhibition process. Dipole moment μ is related to the distribution of electrons in a molecule. It is defined as the product of magnitude charge on the atoms and the distance of separation between the two bonded atoms.

The total dipole moment reflects only the global polarity of a molecule. For the complete molecule the total molecular dipole moment can be estimated as the vector sum of individual bond dipole moments.

A survey of the literature reveals no general agreement on the correlation between the dipole moment and inhibition efficiency values according to some authors. There are reports indicating that lower values of the dipole moment \(\mu\) will favor the inhibitor accumulation in the surface layer, thus increasing the inhibition effectiveness. In some cases, great dipole moment increases the adsorption on the metal surface, which in turn leads to higher inhibition effectiveness. In the current work streptomycin has a lower value of dipole moment \(\mu\) than tetracycline and thus higher inhibition efficiency.

Molecular volume (MV) demonstrates possible metal surface coverage by the inhibitor molecules. The compound that has large MV value has the highest coverage of surface and might give a suitable protection to the metal surface. The efficiency of inhibition speeds up as the volume of the molecules increases due to the enhancement of the contact area between the surface and the molecule. A comparison of the MV values across structures emphasize the order I > II. The trend in the MV amounts is compatible well with the experimentally determined inhibition efficiencies.

4.2 Molecular Dynamics Simulation

In this study, two selected inhibitors have been placed on the Al (1 1 0) surface to find out their suitable configuration. If the system has reached an equilibrium state the fluctuations of temperature and energy should be limited to 5–10%. Figures. 5 and 6 show temperature and energy fluctuation curve with respect to the simulation time, the temperature fluctuates in a range of (298 ± 5) K and the fluctuation of energy is less than 0.5%, indicating that the system has reached an equilibrium state (Shahraki et al. 2016; Zeng et al. 2011). The system equilibrium state and the best adsorption configuration for the inhibitor molecules on aluminum surface are depicted in Fig. 7. The calculated interaction energy obtained from molecular dynamics simulation was displayed in Table 4.

Fig. 5
figure 5

Temperature equilibrium curve obtained from molecular dynamics simulation for I and II

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Fig. 6
figure 6

Energy fluctuant curve obtained from molecular dynamics simulation for I and II

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Fig. 7
figure 7

Equilibrium adsorption configurations of streptomycin (a) tetracycline (b) on Al (1 1 0) surface obtained by molecular dynamics simulations

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Table 4 The interaction energy obtained from MD simulation for adsorption of inhibitors on Al (1 1 0) surface
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Radial distribution functions [RDFs (g(r))] calculation from molecular dynamics trajectory data is an analysis of common and computationally expensive task. As a basic rule, the peak in the g(r) curve within 3.5 Å can be caused with using chemical bonds, and that outside 3.5 Å is caused through coulomb and van der Waals interactions (Zeng et al. 2011).

After analyzing the MD simulation results of inhibitors with aluminum crystal surface, the radial distribution function (g(r)), were obtained (see Fig. 8). As shown in Fig. 8, It can be seen from that the distance between I(N–Al) and II(N–Al) are less than 3.5 Å, which showed that chemical bonds have formed between these two corrosion inhibitors and aluminum atoms. However, it is observed from Fig. 8 that the N–Al and O–Al distance in I/Al system is less than that in II/Al system, indicating the stronger interaction of I inhibitor with aluminum surface than II inhibitor.

Fig. 8
figure 8

Radial distribution functions of nitrogen and oxygen atoms from the three inhibitors on Al (1 1 0) surface in water solution

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The distance between inhibitor and the Al atom indicates the strength of the interactions between the metal and the inhibitor; a shorter distance directs stronger interactions while a longer distance shows weaker interactions. The interaction energy between the metal and the inhibitor is tabulated in Table 4. As can be seen, that the trend follows the order; streptomycin–Al > tetracycline–Al, which confirm that streptomycin has the strongest interaction with the metal surface. It is evident that values of E int are negative for two inhibitors implying that the adsorption on aluminum surface is spontaneous. Furthermore, from a thermodynamic point of opinion, the more stable system has the lowest energy state. Therefore, we expect that the more stable formed complex can have the lower values of E int.

As can be seen, that the trend of values of E int follows the order; I–Al > II–Al, which confirm that I has the strongest interaction with the metal surface. These results are supported through the comparison of the bond distances that show that I–Al has the shortest bond distance (therefore stronger interactions between I and the Al atom), while II–Al has the longest bond distance. Both results (the energy of interaction and the bond distances), approve that I has a stronger adsorption on the metal surface.

As can be seen from Fig. 7, molecules of inhibitor have the parallel orientation with respect to the aluminum surface. The parallel adsorption configurations ensure that the aluminum surface can be maximally covered by the investigated inhibitor molecules.

Both results (DFT and MD simulations), approve that streptomycin has a stronger adsorption on the metal surface.

Accordingly, the classification of these two inhibitors based on the theoretical study is in quite a good agreement with the reported experimental efficiencies for corrosion inhibition.

5 Conclusions

  • The Aluminum corrosion behavior was considered in HCl aqueous solution with and without addition of inhibitor (streptomycin and tetracycline) using techniques of weight loss, Tafel polarization and SEM; and also, molecular dynamics method and quantum chemical calculations. Both inhibitors adsorption on the surface of aluminum sheet obeyed the adsorption isotherm of Temkin model. The negative value for adsorption free energy (∆G ads), indicated that the adsorption of inhibitors could be a spontaneous process. The SEM micrographs confirm the protection of aluminum by tetracycline and streptomycin in acidic media.

  • The obtained quantum chemical data such as E HOMO, (η), \((\chi ),\) the molecular surface area, (MV), (\(\mu\)), \((\alpha )\) and \( (\Delta N) \) are in good agreement with the inhibition efficiencies that were resulted from our experimental results. Molecular dynamics simulations were useful to find the most stable configuration and adsorption energies for streptomycin and tetracycline molecules on the Al (1 1 0) surface. The interaction energy followed the order: streptomycin–Al > tetracycline–Al. Molecules of inhibitor have the parallel orientation with respect to the aluminum surface.

  • This study shows a suitable correlation between the theoretical and experimental data which confirms the reliability of the quantum chemical methods and molecular dynamics simulations for studying the bio-inhibition of corrosion on metal surfaces.